• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1039-1041
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• 2003

Ocean color products derived from remote sensing satellite data are useful for monitoring the sea water quality such as the concentrations of chlorophyll, sediments and dissolved organic matter. Currently, ocean color products derived from MODIS data can be requested from NASA over the internet. However, due to the bandwidth limitation of most users in this region, and the time delay in data delivery, the products cannot be use for near-real time monitoring of sea water chlorophyll. CRISP operates a MODIS data receiving station for environmental monitoring purposes. MODIS data have been routinely received and processed to level 1B. We have adapted the higher level processing algorithms from the Institutional Algorithms provided by NASA to run in a standalone environment. The implemented algorithms include the MODIS ocean color algorithms. Seasonal chlorophyll concentration composite can be compiled for the region. By comparing the near-real time chlorophyll product with the seasonal composite, anomaly in chlorophyll concentration can be detected.

• Journal of Environmental Science International
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• v.15 no.1
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• pp.59-66
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• 2006

High concentration of chlorophyll a occurred around the Ulleung Warm Eddy off Ulleung Island in the East Sea of Korea in spring season. The abnormal distributions of chlorophyll a were captured by satellite remote sensing and measured field data. The temporal and spatial scale of the abnormal distributions were around 20days and 50km diameter off Ullung Island. The anomalies were quantified b)'estimated chlorophyll a derived from OCM and SeaWiFS ocean color data from 2000 to 2004. The origin of abnormal hish concentrations was estimated by this study. It was that suspended material discharged from the Nakdong River and the coastal water located in the southeastern part of Korean Peninsula moved to northeastern coast, and then moved to off Ullung island, The high chlorophyll a concentrations including inorganic materials were accumulated by anticyclonic eddy such as the Ullung Warm Eddy around Ullung island in the East Sea of Korea in spring season.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.635-651
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• 2012

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

• Proceedings of the KSRS Conference
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• v.2
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• pp.918-921
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• 2006

The short-term variation of sea surface temperature before and after typhoons and increase of chlorophyll a concentration that accompany with the typhoons during summer in the East/Japan Sea were explored by satellite. Four typhoons (NAMTHEUN, MEGI, CHABA and SONGDA) and a typhoon (NABI) passed over the East/Japan Sea in 2004 and 2005, respectively. Decreasing of SST was observed in the every five typhoons, however the magnitude of SST decreasing were various from 1 to $5^{\circ}C$. Chlorophyll a increases were found after the typhoons (0.1-3 ${\mu}g$ $l^{-1})$ except NAMTHEUN, and the area was approximately included in SST decreasing area by the typhoons. It suggests that chlorophyll a increase was caused by nutrient input from subsurface layer by strong mixing. On the other hand, rarely chlorophyll a increase was observed in northern area of polar frontal zone, which is located in $38-41^{\circ}N$, than northern area, and chlorophyll a increase in coastal area was higher (more than 3 times) than offshore area. It might suggest that chlorophyll a increase in the East/Japan Sea is also related with the depth or nitracline depth that affects the amount of nutrients supply to the upper layer by typhoon mixing.

• Proceedings of the KSRS Conference
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• v.1
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• pp.82-85
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• 2006

The Geostationary Ocean Color Imager (GOCI) will be loaded in Communication, Ocean and Meteorological Satellite (COMS). To efficiently apply the GOCI data in the variety of fields, it is essential to develop the standard algorithm for estimating the concentration of ocean environmental components (, , and ). For developing the empirical algorithm, about 300 water samples and in situ measurements were collected from sea water around the Korean peninsula from 1998 to 2006. Two kinds of chlorophyll algorithms are developed by using statistical regression and fluorescence technique considering the bio-optical properties in Case-II waters. The single band algorithm for is derived by relationship between Rrs (555) and in situ concentration. The CDOM is estimated by absorption coefficient and ratio of Rrs(412)/Rrs(555). These standard algorithms will be programmed as a module of GOCI Data Processing System (GDPS) until 2008.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.95-100
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• 1998

The purpose of this study is to describe the change of the spring bloom and oceanographic condition. The variation of pigment concentration derived from the satellite ocean color data has been analyzed. According to the movement of blooming area, blooming was very concerned with a rising trend of sea surface temperature and a supply of nutrients. A nutrient rich water carried by the Oyashio encounters with the warm Core ring, where mixings and blooms are observed. We examined the correlation by using the satellite observations of the temperature and chlorophyll-a for the spring seasons (May, June, July) of 1998 the off Sanriku area (38-43N, 141- l50E). Using the SeaWiFS data, we process the data into the level-3, which contains the geophysical value of chlorophyll-a. And chlorophyll-a data is mapped for the water between 110E and 160E, and 15N and 52N with a 0.08 * 0.05 degree grid for each image. And Sea Surface Temperature (SST) data is produced using the AVHRR onboard the NOAA. The SST is derived by the MCSST. Then, the data is mapped for the water as much as chi-a data. And these gridded image was made by detection of each water masses, which are Kuroshio Extension, the warm-core ring and the Oyashlo Intrusion, etc., using those satellite images to determine short term change. Off Sanriku is a place where warm-water pool and the Oyashio at-e mixed. When warm streamer has intruded in cold water, the volume of phytoplankton increases at the tip of warm streamer. Warm water streamer was trigger of occurring blooming. And also, SeaWiFS images provided as much information for the studies of chlorophyll-a concentrations in the surface.

• Ocean and Polar Research
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• v.35 no.2
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• pp.147-155
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• 2013

The purpose of this study is to investigate seasonal difference in linear trends in satellite-derived chlorophyll-a concentration (Chl-a) and their related environmental changes in the South Sea of Korea (SSK) and East China Sea (ECS) for recent 15 years (Jan. 1998~Dec. 2012) by analyzing climatological data of Chl-a, Rrs(555), sea surface wind (SSW) and nutrient. A linear trend analysis of Chl-a data reveals that, during recent 15 years, the spring bloom was enhanced in most of the ECS, while summer and fall blooms were weakened. The increased spring (Mar. - May) Chl-a was associated with strengthened winter (Dec. - Feb.) wind that probably provided more nutrient into the upper ocean from the deep. The causes of decreased summer (Jun. - Aug.) Chl-a in the northern ECS were uncertain, but seemed to be related with the nutrient limitation. Recently (after 2006), low-salinity Changjiang diluted water in the south of Jeju and the SSK had lower phosphate that caused increase in N/P ratio with Chl-a decrease. The decreased fall (Sep. - Nov.) Chl-a was associated with weakened wind that tends to entrain less nutrient into the upper ocean from the deep. This study suggests that phytoplankton in the ECS differently changes in response to environmental changes depending on season and region.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.189-207
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• 2010

Several ocean color algorithms have been developed for GOCI (Geostationary Ocean Color Imager) using in-situ bio-optical data sets. These data sets collected around the Korean Peninsula between 1998 and 2009 include chlorophyll-a concentration (Chl-a), suspended sediment concentration (SS), absorption coefficient of dissolved organic matter ($a_{dom}$), and remote sensing reflectance ($R_{rs}$) obtained from 1348 points. The GOCI Chl-a algorithm was developed using a 4-band remote sensing reflectance ratio that account for the influence of suspended sediment and dissolved organic matter. The GOCI Chl-a algorithm reproduced in-situ chlorophyll concentration better than the other algorithms. In the SeaWiFS images, this algorithm reduced an average error of 46 % in chlorophyll concentration retrieved by standard chlorophyll algorithms of SeaWiFS. For the GOCI SS algorithm, a single band was used (Ahn et al., 2001) instead of a band ratio that is commonly used in chlorophyll algorithms. The GOCI $a_{dom}$ algorithm was derived from the relationship between remote sensing reflectance band ratio ($R_{rs}(412)/R_{rs}(555)$) and $a_{dom}(\lambda)$). The GOCI Chl-a fluorescence and GOCI red tide algorithms were developed by Ahn and Shanmugam (2007) and Ahn and Shanmugam (2006), respectively. If the launch of GOCI in June 2010 is successful, then the developed algorithms will be analyzed in the GOCI CAL/VAL processes, and improved by incorporating more data sets of the ocean optical properties data that will be obtained from waters around the Korean Peninsula.

• Proceedings of the KSRS Conference
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• v.1
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• pp.122-125
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• 2006

The distribution of phytoplankton pigments were studied bimonthly at four stations from the mouth of Mahanadi River at Paradip to the 36.7km off coast in Bay of Bengal during April 2001 to December 2002. Bottom depth was shallower than 40m in all stations. The pigment concentration of Chl-a was measured. It increased from surface to bottom in the water column. The water column integrated chlorophyll-a concentration (Chl-a) varied between 6.1 and $48.5mg{\cdot}m-^2$ with peaks during monsoon period (Aug & Oct). Spatial distribution of salinity depended strongly on freshwater runoff. The salinity was 5psu at river mouth and 25.15psu at offshore in monsoon period; however it was 30psu at the river mouth in summer. We found a linear relationship between the amount of river discharge and integrated Chl-a in coastal region from 2 years observations. Extending this result, we analyzed rainfall and coastal Chl-a using satellite data. The relationship between the river discharge and monthly accumulated rainfall estimated from TRMM and others data sources was analyzed in 2001 and 2002 using Giovanni infrastructure provided by NASA. The result depended on the specified area on TRMM images; the river delta area had sharper relationship than wider rain catchments area. Moreover, the relationship between monthly averaged Chl-a derived from SeaWiFS and monthly accumulated rainfall estimated from TRMM was analyzed from 1998 to 2005. It was clear that the broom in monsoon period was strongly controlled by rainfall on river delta.

• Ocean and Polar Research
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• v.34 no.2
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• pp.201-218
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• 2012

The purpose of this study is to investigate climatological variations from the sea surface temperature (SST), chlorophyll-a concentration (Chl-a), and phytoplankton size class (PSC), using NOAA AVHRR, SeaWiFS, and MODIS data in the South Sea of Korea (SSK) and East China Sea (ECS). 26-year monthly SST and 13-year monthly Chl-a and PSC data, separated by whole and nine-different areas, were used to understand seasonal and inter-annual variations. SST and Chl-a clearly showed seasonal variations: higher SST and Chl-a were observed during the summer and spring, and lower values occurred during the winter and summer. The annual and monthly SST over 26 years increased by $0.2{\sim}1.0^{\circ}C$. The annual and monthly Chl-a concentration over 13 years decreased by $0.2{\sim}1.1mg/m^3$. To determine more detailed spatial and temporal variations, we used the combined data with monthly SST, Chl-a, and PSC. Between 1998 and 2010, the inter-annual trend of Chl-a decreased, with decreasing micro- and nano-size plankton, and increasing pico-size plankton. In regional analysis, the west region of the study area was spatially and temporally correlated with the area dominated by decreasing micro-size plankton; while the east region was less sensitive to coastal and land effects, and was dominated by increasing pico-size plankton. This phenomenon is better related to one or more forcing factors: the increased stratification of ocean driven by changes occurring in spatial variations of the SST caused limited contributions of nutrients and changed marine ecosystems in the study area.